Infrastructure for your workload

Rent Dedicated GPU Servers

Dedicated GPU servers are the optimal solution for AI development, machine learning, big data processing, video rendering, image recognition, and 3D graphics workflows. We provide powerful GPU accelerators (A-Series, and more) in highly secure, low-latency data center with guaranteed bandwidth and reliability.

Configuration catalogue in preparation

Plans will be available later

Explore the service and choose a location. Available configurations, prices and ordering terms will be published with the plans.

GPU servers

What to consider before choosing

Resources for your workload

Match CPU, memory and storage to your application. Final specifications will be listed with each plan.

Location near your users

Consider your audience, connections to other services and data location requirements.

Operating requirements

Check available operating systems, server management, backups and support terms before ordering.

Our GPU servers are ideal for both independent developers and large-scale enterprise solutions. You gain full control over your environment, the ability to process massive datasets, and the performance needed for intensive computing. Customize your setup:

Choose GPU architecture and models (RTX, A100, etc.)
Define the number of GPUs per server
Select CPU, RAM, and storage options
Configure bandwidth and network performance to fit your workload.

Benefits of a Dedicated GPU Server

Compared to traditional servers or VPS, GPU-powered solutions provide:

Major performance boosts for parallel processing tasks
Support for training and deploying deep neural networks
High-speed graphics, video, and data processing
Resource isolation and full flexibility to install any OS or software stack.

Before you order

When will plans be available?

Configurations and prices are being prepared. They will appear on this page when the catalogue is published.

Can I order a server now?

Ordering is not yet available on this page. Terms and ordering links will be published together with the plans.

How should I choose a configuration?

Start with your application requirements: CPU or GPU, memory, storage workload and user location. Then compare them with the published configurations.